Evidence map›Paper›PMID 37238942›Full record

ArticleBiomedicines2023

Identification of New Key Genes and Their Association with Breast Cancer Occurrence and Poor Survival Using In Silico and In Vitro Methods.

Rafat Ali, Armiya Sultan, Romana Ishrat, Shafiul Haque, Nida Jamil Khan, Miguel Angel Prieto

Open access · goldAbstract read
In one paragraph

Article in Biomedicines, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
6.5field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 25 citations in OpenAlex.

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  8. Prognostic value ofHeliyon · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 5 countries.

Rafat AliDepartment of Biosciences, Jamia Millia Islamia (A Central University), New Delhi 110025, India.
Armiya SultanDepartment of Biosciences, Jamia Millia Islamia (A Central University), New Delhi 110025, India.ORCID 0000-0001-5373-8824
Romana IshratCenter for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia (A Central University), New Delhi 110025, India.
Shafiul HaqueResearch and Scientific Studies Unit, College of Nursing and Allied Health Sciences, Jazan University, Jazan 45142, Saudi Arabia.ORCID 0000-0002-2989-121X
Nida Jamil KhanDepartment of Biosciences, Jamia Millia Islamia (A Central University), New Delhi 110025, India.
Miguel Angel PrietoNutrition and Bromatology Group, Department of Analytical Chemistry and Food Science, Faculty of Science, Universidade de Vigo, E32004 Ourense, Spain.ORCID 0000-0002-3513-0054
Jamia Millia Islamia · INAjman University · AEUniversidade de Vigo · ES

Funding

Indian Council of Medical Research BMI/11/(35)/2020MICINN the Ramón y Cajal grant RYC-2017-22891
6 · The paper itself

Abstract

Breast cancer is one of the most prevalent types of cancer diagnosed globally and continues to have a significant impact on the global number of cancer deaths. Despite all efforts of epidemiological and experimental research, therapeutic concepts in cancer are still unsatisfactory. Gene expression datasets are widely used to discover the new biomarkers and molecular therapeutic targets in diseases. In the present study, we analyzed four datasets using R packages with accession number GSE29044, GSE42568, GSE89116, and GSE109169 retrieved from NCBI-GEO and differential expressed genes (DEGs) were identified. Protein-protein interaction (PPI) network was constructed to screen the key genes. Subsequently, the GO function and KEGG pathways were analyzed to determine the biological function of key genes. Expression profile of key genes was validated in MCF-7 and MDA-MB-231 human breast cancer cell lines using qRT-PCR. Overall expression level and stage wise expression pattern of key genes was determined by GEPIA. The bc-GenExMiner was used to compare expression level of genes among groups of patients with respect to age factor. OncoLnc was used to analyze the effect of expression levels of

Indexed as

breast cancerdifferentially expressed genesdown regulated genespoor survivalup regulated genes

Identifiers

PMID37238942
PMCPMC10216146
OpenAlexW4366986663

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.